Sentence examples for frequently accurate from inspiring English sources

In the Y-axis Pr (43 %) and Ls (36%%) were the most frequently accurate landmarks (error <0.5 mm).

The most frequently accurate values were obtained using IOM-HW, which predicted REE within 15% accuracy for 55% (17/31) of boys.

To the Editor: In the field of malaria epidemic early warning, there exists an unfortunate but frequently accurate perception that health systems in many affected countries learn of epidemics by way of the popular press rather than through formal disease surveillance systems.

Two new iPhones at once would seem to represent a new level of difficulty for Apple's supply chain, but frequently-accurate analyst Ming-Chi Kuo said earlier today that Apple could replace the iPhone 5 entirely with the iPhone 5C (or whatever it ends up being called), making it likely that a lot of the production processes from that device would be shifted into place for the low-cost variant.

Both flexible systems underrepresented the physical findings of LPR compared to the rigid examination, but the FO system was frequently more accurate than the DC system.

Trump's press secretary, who frequently calls accurate but critical reporting "fake," is sharing doctored video produced by InfoWars, a lunatic conspiracy theory outlet who has falsely claimed that the Sandy Hook massacre was faked & that John Kerry shot a hurricane with a laser.

Although the PHQ-9 is a frequently-used, accurate measure of depression, it doesn't differentiate between symptoms of anxiety which is characterized by chronic worry about all sorts of life problems and circumstances and symptoms of depression which cover a very wide range of problems, from short periods of low mood to a lifetime of mind-numbing inability to function.

These have to be checked frequently, because however accurate the log or airspeed indicator and compass, the track of a ship or aircraft is not the same as its course.

A lamellar model provides a simple picture that frequently leads to accurate predictions and indicates when mixing effects are important.

A common issue with rule mining approaches is the loss in performance from the statistical model itself; information can be lost during the extraction step and the resultant interpretable models are frequently not as accurate as the original model resulting in a trade-off between rule clarity and accuracy [8].

These approaches are costly, not easily scalable to high throughputs and are frequently not completely accurate.